Abstract
Browsers and other multi-tab applications discard tabs when there is insufficient memory. When a tab has been discarded, the user is forced to reload the tab to continue interaction. Selection of tabs to discard can be based on simple heuristics; however, such selection can lead to discarding tabs that the user is likely to use. Incorrectly discarded tabs are disruptive to users. This disclosure describes the use of machine learning techniques to generate more accurate predictions to select the tab to be discarded. Selectively discarding tabs in this manner can improve memory management while also providing a better user experience.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Napper, Jon; Giuffrida, Michael; Zhao, Guoxing; Amarilio, Omri; Chung, Grace; and Granito, Greg, "Memory Management Using Tab Discard and Reload Prediction", Technical Disclosure Commons, (March 19, 2020)
https://www.tdcommons.org/dpubs_series/3035